Information Spillover, Volatility and the Currency Markets
Bibliographic record
Abstract
We use an impulse response methodology to analyse the effects of U.S. macroeconomic news announcements on the volatilities of three major exchange rates (Euro, Pound Sterling and Yen). Our data consist of 5 minute returns on exchange rates as well as the times of news announcements. In the definition of impulse responses, we allow for different types of news, and consider two categories in the application: those considered positive or negative for the U.S. economy. Using a multivariate GARCH model with exogenous news effects, we find that the initial impact of positive news on the volatility of the Pound is higher than that of the Euro, whereas the persistence of shocks is highest for the Yen. For negative news, we find that an important part of the impact on the Yen and Pound is induced by volatility spillover from the Euro.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".